Digital Divide – Part Two

UPDATE 4/21/18


I wrote the original post (Below) and posted it on April 1st. I later found an article dated March 28, 2018, on the site “Tech Insider”.

While this tidbit is only a very small slice of the future it speaks to the partisan divide in this country (I am working on a post regarding that topic for

It also speaks to the information that I found that I portray as a ‘war’ that has only just begun (below). Back in the day of VHS and Betamax, of CDs and DVDs when, after the initial battles for supremacy, different vendors were able to come together and eventually do what was right for the consumer.

That appears to be not the case today and going for into the realm of ‘new’ technology. As things stand now, Apple, Google, Amazon each have their own services for TV and video. Apple’s won’t work with Google’s devices, Amazon’s won’t work with Apple’s or Google’s (except that Amazon Prime will now work with Apple TV (as of December 2017).

Each tech giant knows that whoever captures the most initial customers will no doubt keep them going into the future. If you owned Apple TV and speakers why would you buy additional speakers from Google when they won’t work with the ones that you currently own?

The future does look bleak indeed if there will not be any interoperability of devices. Hopefully, there will be more Rokus. It will play any product from any of the vendors. The result? It has a more market share than any of the others!

Will the others learn from this?

Date 4/01/2018

This is the second part of a post on how business is responding to the new technology of machine learning, where the new technology will lead, and which business will be the big winner of this next transformation.

In part one we looked at the profound changes coming among them that 47% of jobs will be lost. We looked at how machine learning is going to be the staple of business until Quantum Computers are online.

We looked at a Harvard Business School study “The Digital Business Divide – Analyzing the operating impact of digital transformation” that compared margins, earnings before taxes, and profits for businesses that have adopted digital technologies, the digital leaders to the digital laggards that already may be shut out of the biggest rewards.

We examined David Pring-Mills interviews with Dr. Kai-Fu-Lee a Taiwanese venture capitalist and Mr. Erik Cambria. Both men seemed to have a dark view of companies and vendors that claim to be purveyors of Artificial Intelligence.

I hijacked part of a booklet by PricewaterhouseCoopers which is a thorough examination of the types of artificial intelligence: assisted, augmented, and autonomous. I highly recommend this booklet “ A revolutionary partnership – How AI is pushing man and machine closer together. Consumer Intelligence Series.”

I closed with a short piece regarding The New York Times. The Times editors have relaunched “At War” in March 2018. It is a blog written by Vets for Vets. In addition to having more credibility since the posts are written by combat veterans, the blog also launched the journalism careers of several of its contributors.

Machine Learning Disrupting Digital Enterprises Google Images
Machine Learning Disrupting Digital Enterprises

The Next Great Thing

So what does the future hold? New opportunities will abound. With 47% of jobs lost in the US alone (35% in the UK and 50% in Japan), technological tinkerers will come up with something right? Universal Basic Income will give some relief but the game and pressure to come up with the NGT (Next Great Thing) will be played by thousands if not millions.

Surely, The Singularity will be the incubator for the NGT. Surely, Quantum Computing will lend itself to the discovery of the NGT. Remember these games are already controlled by the Big Six, plus IBM and MedTech companies.

I sure can paint a bleak future for those people just itching to be the next Bill Gates, Paul Allen, Larry Page, Jeff Besos. But I never was good at predicting when a really new and unique device would appear that I just had to have it let alone predict who would have thought up the device.

I will leave the NGT up to the future to decide. The future can be fickle though. Remember when email was a thing of the past? Google is now promoting AMP email as web pages so that all of the fancy footwork that websites can do email will be able to do also. Ah well. We will have to wait for history to tell the tale.

Grab Hold of the Future

Are you casting about to gain knowledge and skills of the future? Are you tired of searching through volumes of literature to find ‘the one’? That one kernel that propels you into your future?

You may want to check out Enterprise.nxt by Hewlett Packard Enterprises. The list of topics includes: “Artificial Intelligence makes flash storage predictive”; Expert Guide to Running Hybrid IT”; The Ethics of AI:  Tool, Partner or Master?”; “What Senior Tech Execs wish they learned earlier in their careers”; “5 Surefire cloud security certifications to boost your career”.

Bringing them Together – last post and this one

Artificial Intelligence and Machine Learning will revolutionize business and marketing more than television, the internet, and mobile have done.

Companies will need a lot of data to use machine learning to streamline its processes, unlock user insights and engage users in new ways. Consumers provide the data to drive these categories. Massive amounts of data are generated because consumers are using multiple devices, across multiple platforms.

85% of executives believe that AI will allow their companies to obtain or sustain competitive advantage. (The Boston Consulting Group “Is your Business Ready for Artificial Intelligence?” September 2017)

In fact, a study indicates that one-third of the time spent in the workplace involves collecting and processing data. (McKinsey & Company, “Where Machines Could Replace Humans-and Where They Can’t (Yet)” July 2016)

Machine learning can analyze millions of data points, and with the software can make smart decisions optimized for an individual business. This will free time so managers can focus on strategic tasks.

A business can determine its objectives, define and quality its audience and then let the software and the data from machine learning figure out how and where to engage the prospects.

A business used to define a core demographics as men aged 35 to 54.

Machine learning will take into account what you want to accomplish with that demographic such as a sale of a product.

But you have to do your homework. You can’t be a laggard so you will have already parsed your metrics such as who are the people that are your most valuable customers. Once you know those characteristics you can have the software look for millions of signals to find people who match the same profiles you have identified.

An example is Trivago.

The online travel company wanted to drive transactions from high-quality users that already used it app. Using Google-powered Univeral App campaigns, machine learning focused on optimizing the use of the app for these specific customers.

The company saw a 20% increase in high-quality user purchases. Machine learning can also determine the most effective ways to engage your high-value users. Think of being able to match the right user, to the right message, to the right creative and at the right time.

Google’s own experience of the right combination of the right message of the right creative at the right time at the right audience resulted in a 50% higher lifetime value for people using YouTube.

The capabilities of machine learning will be critical to personalizing user experiences and thus improve responses.

The caveats will be: First the company will need millions of data points (more on that later). Then it will need the right metrics on what it wants to accomplish  (no sloppy thinking allowed). Then it will need to continuously optimize the customer journey (no one-off shots will work).

It is easy to say. I used to tell waitresses and managers that I worked with that all they had to do was show up and do their job. No longer. Machine learning will enable managers to quantify what is driving each buying decision.

Who is Going to Divide Up the Spoils

(Peter Burrows Laptop Magazine March 2018 MIT Review March 22, 2018)

The First Skirmishes

For the past three years, a battle has been raging. This battle is just the first volley of the first skirmish of a war to end all wars.

It is probable that the winner of this war will amass riches beyond the wildest imagination and will reign as king for decades to come.

This war is being fought for control of the future. Machine learning is the key. Each warrior is adept at producing algorithms to capture the results of machine learning.

But machine learning begins at the beginning. Whoever has the most data has the best chance of winning. Machine learning chomps thru data like the original PacMan games.

This skirmish has pitted Amazon, Google, and Microsoft at the edge of technology. Like standing on the edge of a starship looking over the expanse of blackness who is going to capture the plums.

At the Edge of the Abyss Google Images
At the Edge of the Abyss

Recent skirmishes have involved facial recognition and language translation. Each company is getting good enough in each category but the first plum is still to come. Who can turn the knowledge learned in creating these awesome skills into creating the AI based platforms that will be used to power the new generation?

“Machine learning is where the relational database was in the early 1990’s: everyone knew it would be useful for essentially every company, but very few companies had the ability to take advantage of it”. This quote is from Swami Sivasubramanian, the head of Amazon’s AI division.

Amazon, Google, Microsoft and let’s not forget Tencent, Alibaba and Baidu (we must assume they are playing this war game mustn’t we?), have massive computing resources and armies of talent required to build an AI utility. They all must win this war. To not win is to lose.

“Ultimately, the cloud is how most companies are going to make use of AI-and how technology suppliers are going to make money off of it”, says Nick McQuire and analyst with CSS Insight.

“AI could double the size of the $260 billion cloud market in the coming years”, adds Rajen Sheth, senior director of product management in Google’s Cloud AI unit.

Data is KING KEY

The first part of the key to everything is data. The nature of machine learning is that the more data a system has, the better the decisions it will make.

The second part of the key is that customers are more likely to get locked into an initial vendor and stay put. What company would be foolish enough to spend bundles of money on data and the developments that arise from machine learning only to ditch it in favor of another? Start over? Not very likely I think.

I think the lessons of the rise of computers were well learned. Who gets there first wins! Internet browser, office programs, enterprise software. These companies have been on a battlefield similar to this one before.

Arun Sundararajan studies digital technologies and how they affect the economy at NYU’s Stern School of Business. He states that “the prize will be to become the operating system of the next era of tech”.

Puneet Shivam, president of Avendus Capital US, an investment bank says: “The leaders of the AI Cloud will become the most powerful companies in history”.

Enterprise software companies such as Oracle, Salesforce, and SAP are already embedding machine learning into their apps. Think then of the thousands of AI wannabes that are in hot pursuit! Pitched warfare is on the horizon.

We see that Amazon, Google, and Microsoft (don’t forget Alibaba, Tencent, and Baidu) all offer services in facial recognition, in turning speech into text and vice versa for building the natural-language processing that allows Alexa, Siri, Cortana, and other digital assistants to understand your queries.

I receive online job requests from companies such as APPEN Global and WhatUsersDo. These companies hire independent contractors to perform basic interpersonal communication tasks.

These tasks can be recording voice dialog such as instructions a person would use to direct Siri to do some task. Another task is conversing with another person by reading scripts that would be used to write software for the personal assistants. Each task requires a specified number of submissions which, I assume, is to assure that enough data points are obtained to ensure accurate algorithms can be written.

Remember Microsoft?

How did Microsoft build its empire? Build the platform and build the apps to run on the platform. Apple did it with iOS and mobile apps in its era.

Each company runs the same plays to make machine learning accessible to total AI novices. Amazon unveiled SageMaker which could be used to build machine-learning apps to be not much more complicated than building a website.

A few weeks later Google introduced CloudAutoML.  A company can feed its own unique collection of data into CloudAutoML and this tool will generate a machine-learning mode capable of improving the business.

Google states that more than 13,000 companies have asked to try CloudAutoML.

How Many?

How many organizations in the world could benefit from machine learning? Maybe the real question is how many can hire people with the necessary background and skills to make it work?

Jeff Dean,  head of Google Brain says that “to get even 10 million companies to use machine learning, we have to make this stuff much easier to use”.

Microsoft has been doing breakthrough work on AI such as computer vision and natural language processing for two decades. It has massive amounts of data for use by its Azure cloud including content from Bing, LinkedIn, Skype and the billion people that use Microsoft Office.

Sounds awesome. Google is the R&D guru of AI. It led the way to computers that can beat humans at their own games. It led the way to self-driving cars. It has its own line of chips to run its machine-learning infrastructure.

Thanks to Google Search it probably has access to more data than any other company. According to Alexander Wang, the 20-year-old founder of AI startup Scale, they are in the best position to monetize data and they have the best machine-learning researchers in the world”.

But Amazon is no slouch. A few years ago it burst onto the scene by demonstrating that almost half of its business was from  AWS (Amazon Web Service). Watch for more from Mr. Bezos.

Continuing education:


Education Opportunity


Sample Registration for EMTECH
Sample Registration for EMTECH

We have a home for Veteran’s-Do You?

We have a Home for Veterans, do You?

Edison International Needed!

Medical Foster Care for Veterans Needed!

Frank X. Shaw, Major Marine Corps Reserve 

Microsoft’s commitment to offering deep and focused training before people left the military service led to a training apprenticeship and training program for military personnel at Joint Base Lewis-McChord which is located just 30 minutes south of Microsoft’s corporate headquarters in Redmond, Washington.

The idea was to train these people in skills that were in short supply in the technology industry.

Technical training would be augmented with mentoring from people already in the private sector. The bold name for the pilot program? The Microsoft Software & Systems Academy!

The first class had only 22 service members. It soon became apparent that this training filled a need to help service people transition to civilian careers.

Frank Shaw raised his hand and volunteered to create a new Military Affairs team at Microsoft and be responsible for the future of the program.

On March 21st, 2018 the 14th MSSa location at Camp Lejeune North Carolina began. Each of the almost 1,000 graduates of the course has a story to tell. But the real storyline of Frank’s story is that this program has 280 hiring partners with more coming online all the time. These partners create opportunities for veterans in the technology industry.

To become a hiring partner or get involved, visit


Thanks for stopping by.


In the first part of this post, I promoted the last Blue Moon of 2018. I am going to update how that looked at various parts around the world. Paschal Blue Moon March 31, 2018

These three images of the Blue Moon, March 31, 2018, also known as the Paschal Moon.The images are from I must apologize I lost my notes on the photographers. I know that the moon above the Navesink Twin Lights lighthouse in Highlands, New Jersey. Astrophotographer Steve Scanlon captured this image.

The image in the second row is of the Blue Moon in 2015 captured by Chris Jankowki of Erie Pennsylvania.

The one on the second row right is a jet flying thru the face of the Blue Moon March 31, 2018.

I will continue to scour my notes to find the photographers of the two images so that they get the credit they deserve. So far my Google searches have led nowhere and is not displaying the page that I hijacked these images from. Embarrassing and again, I apologize for not naming the photographers.

The next Blue Moon appears in October 2020. This year we were treated to a rare phenomenon two Blue Moons in a calendar year. The last time it occurred was in 1999. The next occurrence will be in 2037!

So that you have enough images to tide you over until then a last, impressive image captured by Frank Langben of San Jose CA.

March 31, 2018 Blue Moon captured by Frank Langben of San Jose CA.
March 31, 2018, Blue Moon captured by Frank Langbein of San Jose CA.